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<div class="title">TrsmKernel.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// for linear algebra.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Copyright (C) 2022 Intel Corporation</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160; </div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#ifndef EIGEN_TRSM_KERNEL_IMPL_H</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#define EIGEN_TRSM_KERNEL_IMPL_H</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160; </div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &quot;../../InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160; </div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#define EIGEN_USE_AVX512_TRSM_KERNELS </span><span class="comment">// Comment out to prevent using optimized trsm kernels.</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160; </div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">#if defined(EIGEN_HAS_CXX17_IFCONSTEXPR)</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#define EIGEN_IF_CONSTEXPR(X) if constexpr (X)</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#define EIGEN_IF_CONSTEXPR(X) if (X)</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment">// Need this for some std::min calls.</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#ifdef min</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#undef min</span></div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160; </div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> {</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160; </div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#define EIGEN_AVX_MAX_NUM_ACC (24L)</span></div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#define EIGEN_AVX_MAX_NUM_ROW (8L)  </span><span class="comment">// Denoted L in code.</span></div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="preprocessor">#define EIGEN_AVX_MAX_K_UNROL (4L)</span></div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="preprocessor">#define EIGEN_AVX_B_LOAD_SETS (2L)</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="preprocessor">#define EIGEN_AVX_MAX_A_BCAST (2L)</span></div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">typedef</span> Packet16f vecFullFloat;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">typedef</span> Packet8d vecFullDouble;</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">typedef</span> Packet8f vecHalfFloat;</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="keyword">typedef</span> Packet4d vecHalfDouble;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160; </div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="comment">// Compile-time unrolls are implemented here.</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="comment">// Note: this depends on macros and typedefs above.</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &quot;TrsmUnrolls.inc&quot;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160; </div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#if defined(EIGEN_USE_AVX512_TRSM_KERNELS) &amp;&amp; (EIGEN_COMP_CLANG != 0)</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="preprocessor">#define EIGEN_ENABLE_AVX512_NOCOPY_TRSM_CUTOFFS </span><span class="comment">// Comment out to disable no-copy dispatch</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar&gt;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;int64_t avx512_trsm_cutoff(int64_t L2Size, int64_t N, <span class="keywordtype">double</span> L2Cap){</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keyword">const</span> int64_t U3 = 3*packet_traits&lt;Scalar&gt;::size;</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  <span class="keyword">const</span> int64_t MaxNb = 5*U3;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  int64_t Nb = std::min(MaxNb, N);</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  <span class="keywordtype">double</span> cutoff_d = (((L2Size*L2Cap)/(<span class="keyword">sizeof</span>(Scalar)))-(EIGEN_AVX_MAX_NUM_ROW)*Nb)/</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    ((EIGEN_AVX_MAX_NUM_ROW)+Nb);</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  int64_t cutoff_l = <span class="keyword">static_cast&lt;</span>int64_t<span class="keyword">&gt;</span>(cutoff_d);</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  <span class="keywordflow">return</span> (cutoff_l/EIGEN_AVX_MAX_NUM_ROW)*EIGEN_AVX_MAX_NUM_ROW;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;}</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keyword">typename</span> vec, <span class="keywordtype">int</span>64_t unrollM, <span class="keywordtype">int</span>64_t unrollN, <span class="keywordtype">bool</span> remM, <span class="keywordtype">bool</span> remN&gt;</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="keyword">static</span> EIGEN_ALWAYS_INLINE</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;<span class="keywordtype">void</span> transStoreC(PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; &amp;zmm,</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;                 Scalar *C_arr, int64_t LDC, int64_t remM_ = 0, int64_t remN_ = 0) {</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  EIGEN_UNUSED_VARIABLE(remN_);</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  EIGEN_UNUSED_VARIABLE(remM_);</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  <span class="keyword">using</span> urolls = unrolls::trans&lt;Scalar&gt;;</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160; </div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  constexpr int64_t U3 = urolls::PacketSize * 3;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  constexpr int64_t U2 = urolls::PacketSize * 2;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  constexpr int64_t U1 = urolls::PacketSize * 1;</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  static_assert( unrollN == U1 || unrollN == U2 || unrollN == U3, <span class="stringliteral">&quot;unrollN should be a multiple of PacketSize&quot;</span>);</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;  static_assert( unrollM == EIGEN_AVX_MAX_NUM_ROW, <span class="stringliteral">&quot;unrollM should be equal to EIGEN_AVX_MAX_NUM_ROW&quot;</span>);</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  urolls::template transpose&lt;unrollN, 0&gt;(zmm);</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  EIGEN_IF_CONSTEXPR(unrollN &gt; U2) urolls::template transpose&lt;unrollN, 2&gt;(zmm);</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  EIGEN_IF_CONSTEXPR(unrollN &gt; U1) urolls::template transpose&lt;unrollN, 1&gt;(zmm);</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  static_assert( (remN &amp;&amp; unrollN == U1) || !remN, <span class="stringliteral">&quot;When handling N remainder set unrollN=U1&quot;</span>);</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  EIGEN_IF_CONSTEXPR(!remN) {</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    urolls::template storeC&lt;std::min(unrollN, U1), unrollN, 0, remM&gt;(C_arr, LDC, zmm,  remM_);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    EIGEN_IF_CONSTEXPR(unrollN &gt; U1) {</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      constexpr int64_t unrollN_ = std::min(unrollN-U1, U1);</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      urolls::template storeC&lt;unrollN_, unrollN, 1, remM&gt;(C_arr + U1*LDC, LDC, zmm,  remM_);</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    }</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    EIGEN_IF_CONSTEXPR(unrollN &gt; U2) {</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;      constexpr int64_t unrollN_ = std::min(unrollN-U2, U1);</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      urolls:: template storeC&lt;unrollN_, unrollN, 2, remM&gt;(C_arr + U2*LDC, LDC, zmm,  remM_);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    }</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    EIGEN_IF_CONSTEXPR( (std::is_same&lt;Scalar, float&gt;::value) ) {</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;      <span class="comment">// Note: without &quot;if constexpr&quot; this section of code will also be</span></div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      <span class="comment">// parsed by the compiler so each of the storeC will still be instantiated.</span></div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      <span class="comment">// We use enable_if in aux_storeC to set it to an empty function for</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      <span class="comment">// these cases.</span></div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      <span class="keywordflow">if</span>(remN_ == 15)</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        urolls::template storeC&lt;15, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 14)</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        urolls::template storeC&lt;14, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 13)</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        urolls::template storeC&lt;13, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 12)</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        urolls::template storeC&lt;12, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 11)</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;        urolls::template storeC&lt;11, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 10)</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        urolls::template storeC&lt;10, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 9)</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        urolls::template storeC&lt;9, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 8)</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;        urolls::template storeC&lt;8, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 7)</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;        urolls::template storeC&lt;7, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 6)</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        urolls::template storeC&lt;6, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 5)</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        urolls::template storeC&lt;5, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 4)</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        urolls::template storeC&lt;4, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 3)</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        urolls::template storeC&lt;3, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 2)</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        urolls::template storeC&lt;2, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 1)</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        urolls::template storeC&lt;1, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    }</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      <span class="keywordflow">if</span>(remN_ == 7)</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        urolls::template storeC&lt;7, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 6)</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        urolls::template storeC&lt;6, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 5)</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        urolls::template storeC&lt;5, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 4)</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;        urolls::template storeC&lt;4, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 3)</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        urolls::template storeC&lt;3, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 2)</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        urolls::template storeC&lt;2, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span>(remN_ == 1)</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        urolls::template storeC&lt;1, unrollN, 0, remM&gt;(C_arr, LDC, zmm, remM_);</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    }</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  }</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;}</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160; </div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keywordtype">bool</span> isARowMajor, <span class="keywordtype">bool</span> isCRowMajor, <span class="keywordtype">bool</span> isAdd, <span class="keywordtype">bool</span> handleKRem&gt;</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;<span class="keywordtype">void</span> gemmKernel(Scalar *A_arr, Scalar *B_arr, Scalar *C_arr,</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                int64_t M, int64_t N, int64_t K,</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                int64_t LDA, int64_t LDB, int64_t LDC) {</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  <span class="keyword">using</span> urolls = unrolls::gemm&lt;Scalar, isAdd&gt;;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;  constexpr int64_t U3 = urolls::PacketSize * 3;</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  constexpr int64_t U2 = urolls::PacketSize * 2;</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  constexpr int64_t U1 = urolls::PacketSize * 1;</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;  <span class="keyword">using</span> vec = <span class="keyword">typename</span> std::conditional&lt;std::is_same&lt;Scalar, float&gt;::value,</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;                                        vecFullFloat,</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                                        vecFullDouble&gt;::type;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  int64_t N_ = (N/U3)*U3;</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  int64_t M_ = (M/EIGEN_AVX_MAX_NUM_ROW)*EIGEN_AVX_MAX_NUM_ROW;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  int64_t K_ = (K/EIGEN_AVX_MAX_K_UNROL)*EIGEN_AVX_MAX_K_UNROL;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  int64_t j = 0;</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="keywordflow">for</span>(; j &lt; N_; j += U3) {</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    constexpr int64_t EIGEN_AVX_MAX_B_LOAD = EIGEN_AVX_B_LOAD_SETS*3;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    int64_t i = 0;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    <span class="keywordflow">for</span>(; i &lt; M_; i += EIGEN_AVX_MAX_NUM_ROW) {</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)], *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;      urolls::template setzero&lt;3,EIGEN_AVX_MAX_NUM_ROW&gt;(zmm);</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        urolls:: template microKernel&lt;isARowMajor,3,EIGEN_AVX_MAX_NUM_ROW,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      }</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;          urolls:: template microKernel&lt;isARowMajor,3,EIGEN_AVX_MAX_NUM_ROW,1,</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;                                        EIGEN_AVX_B_LOAD_SETS*3,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;      }</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        urolls::template updateC&lt;3,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;        urolls::template storeC&lt;3,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC+ j], LDC, zmm);</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;      }</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U3,false, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC);</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;      }</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    }</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 4) { <span class="comment">// Note: this block assumes EIGEN_AVX_MAX_NUM_ROW = 8. Should be removed otherwise</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;      urolls::template setzero&lt;3,4&gt;(zmm);</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;        urolls:: template microKernel&lt;isARowMajor,3,4,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                                      EIGEN_AVX_B_LOAD_SETS*3,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;      }</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;          urolls:: template microKernel&lt;isARowMajor,3,4,1,</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                                        EIGEN_AVX_B_LOAD_SETS*3,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        }</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      }</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;        urolls::template updateC&lt;3,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;        urolls::template storeC&lt;3,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;      }</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U3,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 4);</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;      }</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;      i += 4;</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    }</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 2) {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;      urolls::template setzero&lt;3,2&gt;(zmm);</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        urolls:: template microKernel&lt;isARowMajor,3,2,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;                                      EIGEN_AVX_B_LOAD_SETS*3,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;      }</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;          urolls:: template microKernel&lt;isARowMajor,3,2,1,</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;                                        EIGEN_AVX_B_LOAD_SETS*3,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        }</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;      }</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        urolls::template updateC&lt;3,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        urolls::template storeC&lt;3,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;      }</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U3,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 2);</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;      }</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;      i += 2;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    }</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    <span class="keywordflow">if</span>(M - i &gt; 0) {</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;      urolls::template setzero&lt;3,1&gt;(zmm);</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;      {</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;        <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;          urolls:: template microKernel&lt;isARowMajor,3,1,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;                                        EIGEN_AVX_B_LOAD_SETS*3,1&gt;(</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;          B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;        }</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;          <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;            urolls:: template microKernel&lt;isARowMajor,3,1,1,</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;                                          EIGEN_AVX_B_LOAD_SETS*3,1&gt;(B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;            B_t += LDB;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;            EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;          }</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;        }</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;        EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;          urolls::template updateC&lt;3,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;          urolls::template storeC&lt;3,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        }</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;        <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;          transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U3,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 1);</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;        }</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;      }</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    }</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;  }</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;  <span class="keywordflow">if</span>(N - j &gt;= U2) {</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    constexpr int64_t EIGEN_AVX_MAX_B_LOAD = EIGEN_AVX_B_LOAD_SETS*2;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    int64_t i = 0;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    <span class="keywordflow">for</span>(; i &lt; M_; i += EIGEN_AVX_MAX_NUM_ROW) {</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)], *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;      urolls::template setzero&lt;2,EIGEN_AVX_MAX_NUM_ROW&gt;(zmm);</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;        urolls:: template microKernel&lt;isARowMajor,2,EIGEN_AVX_MAX_NUM_ROW,</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;                                      EIGEN_AVX_MAX_K_UNROL,EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;      }</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;          urolls:: template microKernel&lt;isARowMajor,2,EIGEN_AVX_MAX_NUM_ROW,1,</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;        }</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;      }</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;        urolls::template updateC&lt;2,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        urolls::template storeC&lt;2,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;      }</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U2,false, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC);</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;      }</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    }</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 4) { <span class="comment">// Note: this block assumes EIGEN_AVX_MAX_NUM_ROW = 8. Should be removed otherwise</span></div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;      urolls::template setzero&lt;2,4&gt;(zmm);</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;        urolls:: template microKernel&lt;isARowMajor,2,4,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;      }</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;          urolls:: template microKernel&lt;isARowMajor,2,4,1,</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;        }</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;      }</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;        urolls::template updateC&lt;2,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;        urolls::template storeC&lt;2,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;      }</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U2,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 4);</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;      }</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;      i += 4;</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;    }</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 2) {</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;      urolls::template setzero&lt;2,2&gt;(zmm);</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;        urolls:: template microKernel&lt;isARowMajor,2,2,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;      }</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;          urolls:: template microKernel&lt;isARowMajor,2,2,1,</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;        }</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;      }</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;        urolls::template updateC&lt;2,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;        urolls::template storeC&lt;2,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;      }</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U2,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 2);</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;      }</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;      i += 2;</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    }</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;    <span class="keywordflow">if</span>(M - i &gt; 0) {</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;      urolls::template setzero&lt;2,1&gt;(zmm);</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;        urolls:: template microKernel&lt;isARowMajor,2,1,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,1&gt;(</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;      }</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;          urolls:: template microKernel&lt;isARowMajor,2,1,1,</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,1&gt;(B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;        }</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;      }</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;          urolls::template updateC&lt;2,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;          urolls::template storeC&lt;2,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;      }</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U2,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 1);</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;      }</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    }</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;    j += U2;</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;  }</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;  <span class="keywordflow">if</span>(N - j &gt;= U1) {</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;    constexpr int64_t EIGEN_AVX_MAX_B_LOAD = EIGEN_AVX_B_LOAD_SETS*1;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;    int64_t i = 0;</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;    <span class="keywordflow">for</span>(; i &lt; M_; i += EIGEN_AVX_MAX_NUM_ROW) {</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)], *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;      urolls::template setzero&lt;1,EIGEN_AVX_MAX_NUM_ROW&gt;(zmm);</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,EIGEN_AVX_MAX_NUM_ROW,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;      }</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,EIGEN_AVX_MAX_NUM_ROW,1,</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;                                        EIGEN_AVX_B_LOAD_SETS*1,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;        }</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;      }</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;        urolls::template updateC&lt;1,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;        urolls::template storeC&lt;1,EIGEN_AVX_MAX_NUM_ROW&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;      }</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,false, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC);</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;      }</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;    }</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 4) { <span class="comment">// Note: this block assumes EIGEN_AVX_MAX_NUM_ROW = 8. Should be removed otherwise</span></div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;      urolls::template setzero&lt;1,4&gt;(zmm);</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,4,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;      }</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,4,1,</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;        }</div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;      }</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;        urolls::template updateC&lt;1,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;        urolls::template storeC&lt;1,4&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;      }</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 4);</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;      }</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;      i += 4;</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    }</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 2) {</div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;      urolls::template setzero&lt;1,2&gt;(zmm);</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,2,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;                                        B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;      }</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,2,1,</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST&gt;(</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;        }</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;      }</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;        urolls::template updateC&lt;1,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;        urolls::template storeC&lt;1,2&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;      }</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 2);</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;      }</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;      i += 2;</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;    }</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;    <span class="keywordflow">if</span>(M - i &gt; 0) {</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;      urolls::template setzero&lt;1,1&gt;(zmm);</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;      {</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;        <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,1,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,1&gt;(</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;                                          B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;          B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;        }</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;        EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,1,1,EIGEN_AVX_B_LOAD_SETS*1,1&gt;(B_t, A_t, LDB, LDA, zmm);</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;        }</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;      }</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;        EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;          urolls::template updateC&lt;1,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;          urolls::template storeC&lt;1,1&gt;(&amp;C_arr[i*LDC + j], LDC, zmm);</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;        }</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;        <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;          transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, false&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 1);</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;        }</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;      }</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;    }</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;    j += U1;</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;  }</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;  <span class="keywordflow">if</span>(N - j &gt; 0) {</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;    constexpr int64_t EIGEN_AVX_MAX_B_LOAD = EIGEN_AVX_B_LOAD_SETS*1;</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;    int64_t i = 0;</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;    <span class="keywordflow">for</span>(; i &lt; M_; i += EIGEN_AVX_MAX_NUM_ROW) {</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;      urolls::template setzero&lt;1,EIGEN_AVX_MAX_NUM_ROW&gt;(zmm);</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,EIGEN_AVX_MAX_NUM_ROW,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;          B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;      }</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,EIGEN_AVX_MAX_NUM_ROW,1,</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;                                          B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;        }</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;      }</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;        urolls::template updateC&lt;1,EIGEN_AVX_MAX_NUM_ROW,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;        urolls::template storeC&lt;1,EIGEN_AVX_MAX_NUM_ROW,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;      }</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,false, true&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 0, N-j);</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;      }</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;    }</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 4) { <span class="comment">// Note: this block assumes EIGEN_AVX_MAX_NUM_ROW = 8. Should be removed otherwise</span></div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;      urolls::template setzero&lt;1,4&gt;(zmm);</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,4,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;                                        B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;      }</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,4,1,</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;                                          B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;        }</div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;      }</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;        urolls::template updateC&lt;1,4,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;        urolls::template storeC&lt;1,4,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;      }</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, true&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 4, N-j);</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;      }</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;      i += 4;</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;    }</div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;    <span class="keywordflow">if</span>(M - i &gt;= 2) {</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;      urolls::template setzero&lt;1,2&gt;(zmm);</div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,2,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;                                        B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;      }</div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,2,1,</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,EIGEN_AVX_MAX_A_BCAST,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;                                          B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;        }</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;      }</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;        urolls::template updateC&lt;1,2,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;        urolls::template storeC&lt;1,2,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;      }</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, true&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 2, N-j);</div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;      }</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;      i += 2;</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;    }</div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;    <span class="keywordflow">if</span>(M - i &gt; 0) {</div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;      Scalar *A_t = &amp;A_arr[idA&lt;isARowMajor&gt;(i,0,LDA)];</div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;      Scalar *B_t = &amp;B_arr[0*LDB + j];</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;      PacketBlock&lt;vec,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; zmm;</div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;      urolls::template setzero&lt;1,1&gt;(zmm);</div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;      <span class="keywordflow">for</span>(int64_t k = 0; k &lt; K_ ; k += EIGEN_AVX_MAX_K_UNROL) {</div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;        urolls:: template microKernel&lt;isARowMajor,1,1,EIGEN_AVX_MAX_K_UNROL,</div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;                                      EIGEN_AVX_MAX_B_LOAD,1,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;                                        B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;        B_t += EIGEN_AVX_MAX_K_UNROL*LDB;</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;        EIGEN_IF_CONSTEXPR(isARowMajor) A_t += EIGEN_AVX_MAX_K_UNROL; <span class="keywordflow">else</span> A_t += EIGEN_AVX_MAX_K_UNROL*LDA;</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;      }</div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;      EIGEN_IF_CONSTEXPR(handleKRem) {</div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;        <span class="keywordflow">for</span>(int64_t k = K_; k &lt; K ; k ++) {</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;          urolls:: template microKernel&lt;isARowMajor,1,1,1,</div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;                                        EIGEN_AVX_MAX_B_LOAD,1,<span class="keyword">true</span>&gt;(</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;                                          B_t, A_t, LDB, LDA, zmm, N - j);</div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;          B_t += LDB;</div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;          EIGEN_IF_CONSTEXPR(isARowMajor) A_t++; <span class="keywordflow">else</span> A_t += LDA;</div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;        }</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;      }</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;      EIGEN_IF_CONSTEXPR(isCRowMajor) {</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;        urolls::template updateC&lt;1,1,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;        urolls::template storeC&lt;1,1,true&gt;(&amp;C_arr[i*LDC + j], LDC, zmm, N - j);</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;      }</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;        transStoreC&lt;Scalar,vec,EIGEN_AVX_MAX_NUM_ROW,U1,true, true&gt;(zmm, &amp;C_arr[i + j*LDC], LDC, 1, N-j);</div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;      }</div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;    }</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;  }</div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;}</div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160; </div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keyword">typename</span> vec, <span class="keywordtype">int</span>64_t unrollM, <span class="keywordtype">bool</span> isARowMajor, <span class="keywordtype">bool</span> isFWDSolve, <span class="keywordtype">bool</span> isUnitDiag&gt;</div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;<span class="keyword">static</span> EIGEN_ALWAYS_INLINE</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;<span class="keywordtype">void</span> triSolveKernel(Scalar *A_arr, Scalar *B_arr, int64_t K, int64_t LDA, int64_t LDB) {</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160; </div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;  static_assert( unrollM &lt;= EIGEN_AVX_MAX_NUM_ROW, <span class="stringliteral">&quot;unrollM should be equal to EIGEN_AVX_MAX_NUM_ROW&quot;</span> );</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;  <span class="keyword">using</span> urolls = unrolls::trsm&lt;Scalar&gt;;</div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160;  constexpr int64_t U3 = urolls::PacketSize * 3;</div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;  constexpr int64_t U2 = urolls::PacketSize * 2;</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;  constexpr int64_t U1 = urolls::PacketSize * 1;</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160; </div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;  PacketBlock&lt;vec,EIGEN_AVX_MAX_NUM_ACC&gt; RHSInPacket;</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;  PacketBlock&lt;vec,EIGEN_AVX_MAX_NUM_ROW&gt; AInPacket;</div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160; </div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;  int64_t k = 0;</div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;  <span class="keywordflow">while</span>(K - k &gt;= U3) {</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;    urolls:: template loadRHS&lt;isFWDSolve, unrollM, 3&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;    urolls:: template triSolveMicroKernel&lt;isARowMajor, isFWDSolve, isUnitDiag, unrollM, 3&gt;(</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;      A_arr, LDA, RHSInPacket, AInPacket);</div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;    urolls:: template storeRHS&lt;isFWDSolve, unrollM, 3&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;    k += U3;</div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;  }</div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= U2) {</div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;    urolls:: template loadRHS&lt;isFWDSolve, unrollM, 2&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;    urolls:: template triSolveMicroKernel&lt;isARowMajor, isFWDSolve, isUnitDiag, unrollM, 2&gt;(</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;      A_arr, LDA, RHSInPacket, AInPacket);</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;    urolls:: template storeRHS&lt;isFWDSolve, unrollM, 2&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;    k += U2;</div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;  }</div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= U1) {</div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;    urolls:: template loadRHS&lt;isFWDSolve, unrollM, 1&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;    urolls:: template triSolveMicroKernel&lt;isARowMajor, isFWDSolve, isUnitDiag, unrollM, 1&gt;(</div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;      A_arr, LDA, RHSInPacket, AInPacket);</div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;    urolls:: template storeRHS&lt;isFWDSolve, unrollM, 1&gt;(B_arr + k, LDB, RHSInPacket);</div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;    k += U1;</div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;  }</div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;  <span class="keywordflow">if</span>(K - k &gt; 0) {</div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;    <span class="comment">// Handle remaining number of RHS</span></div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;    urolls::template loadRHS&lt;isFWDSolve, unrollM, 1, true&gt;(B_arr + k, LDB, RHSInPacket, K-k);</div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;    urolls::template triSolveMicroKernel&lt;isARowMajor, isFWDSolve, isUnitDiag, unrollM, 1&gt;(</div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;      A_arr, LDA, RHSInPacket, AInPacket);</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;    urolls::template storeRHS&lt;isFWDSolve, unrollM, 1, true&gt;(B_arr + k, LDB, RHSInPacket, K-k);</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;  }</div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;}</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160; </div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keywordtype">bool</span> isARowMajor, <span class="keywordtype">bool</span> isFWDSolve, <span class="keywordtype">bool</span> isUnitDiag&gt;</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;<span class="keywordtype">void</span> triSolveKernelLxK(Scalar *A_arr, Scalar *B_arr, int64_t M, int64_t K, int64_t LDA, int64_t LDB) {</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;  <span class="comment">// Note: this assumes EIGEN_AVX_MAX_NUM_ROW = 8. Unrolls should be adjusted</span></div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;  <span class="comment">// accordingly if EIGEN_AVX_MAX_NUM_ROW is smaller.</span></div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;  <span class="keyword">using</span> vec = <span class="keyword">typename</span> std::conditional&lt;std::is_same&lt;Scalar, float&gt;::value, vecFullFloat, vecFullDouble&gt;::type;</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;  <span class="keywordflow">if</span> (M == 8)</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    triSolveKernel&lt;Scalar, vec, 8, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 7)</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;    triSolveKernel&lt;Scalar, vec, 7, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 6)</div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;    triSolveKernel&lt;Scalar, vec, 6, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 5)</div>
<div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;    triSolveKernel&lt;Scalar, vec, 5, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 4)</div>
<div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;    triSolveKernel&lt;Scalar, vec, 4, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 3)</div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;    triSolveKernel&lt;Scalar, vec, 3, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 2)</div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;    triSolveKernel&lt;Scalar, vec, 2, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (M == 1)</div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;    triSolveKernel&lt;Scalar, vec, 1, isARowMajor, isFWDSolve, isUnitDiag&gt;(A_arr, B_arr, K, LDA, LDB);</div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;  <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;}</div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160; </div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keywordtype">bool</span> toTemp = true, <span class="keywordtype">bool</span> remM = false&gt;</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;<span class="keyword">static</span> EIGEN_ALWAYS_INLINE</div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;<span class="keywordtype">void</span> copyBToRowMajor(Scalar *B_arr, int64_t LDB, int64_t K,</div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;                 Scalar *B_temp, int64_t LDB_, int64_t remM_ = 0) {</div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;  EIGEN_UNUSED_VARIABLE(remM_);</div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;  <span class="keyword">using</span> urolls = unrolls::transB&lt;Scalar&gt;;</div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;  <span class="keyword">using</span> vecHalf = <span class="keyword">typename</span> std::conditional&lt;std::is_same&lt;Scalar, float&gt;::value, vecHalfFloat, vecFullDouble&gt;::type;</div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;  PacketBlock&lt;vecHalf,EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS&gt; ymm;</div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;  constexpr int64_t U3 = urolls::PacketSize * 3;</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;  constexpr int64_t U2 = urolls::PacketSize * 2;</div>
<div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;  constexpr int64_t U1 = urolls::PacketSize * 1;</div>
<div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;  int64_t K_ = K/U3*U3;</div>
<div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;  int64_t k = 0;</div>
<div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160; </div>
<div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160;  <span class="keywordflow">for</span>(; k &lt; K_; k += U3) {</div>
<div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;    urolls::template transB_kernel&lt;U3, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;    B_temp += U3;</div>
<div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;  }</div>
<div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= U2) {</div>
<div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;    urolls::template transB_kernel&lt;U2, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;    B_temp += U2; k += U2;</div>
<div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160;  }</div>
<div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= U1) {</div>
<div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;    urolls::template transB_kernel&lt;U1, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;    B_temp += U1; k += U1;</div>
<div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;  }</div>
<div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;  EIGEN_IF_CONSTEXPR( U1 &gt; 8) {</div>
<div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;    <span class="comment">// Note: without &quot;if constexpr&quot; this section of code will also be</span></div>
<div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;    <span class="comment">// parsed by the compiler so there is an additional check in {load/store}BBlock</span></div>
<div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;    <span class="comment">// to make sure the counter is not non-negative.</span></div>
<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;    <span class="keywordflow">if</span>(K - k &gt;= 8) {</div>
<div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;      urolls::template transB_kernel&lt;8, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;      B_temp += 8; k += 8;</div>
<div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;    }</div>
<div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;  }</div>
<div class="line"><a name="l00812"></a><span class="lineno">  812</span>&#160;  EIGEN_IF_CONSTEXPR( U1 &gt; 4) {</div>
<div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;    <span class="comment">// Note: without &quot;if constexpr&quot; this section of code will also be</span></div>
<div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160;    <span class="comment">// parsed by the compiler so there is an additional check in {load/store}BBlock</span></div>
<div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;    <span class="comment">// to make sure the counter is not non-negative.</span></div>
<div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;    <span class="keywordflow">if</span>(K - k &gt;= 4) {</div>
<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;      urolls::template transB_kernel&lt;4, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;      B_temp += 4; k += 4;</div>
<div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;    }</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;  }</div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= 2) {</div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;    urolls::template transB_kernel&lt;2, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00823"></a><span class="lineno">  823</span>&#160;    B_temp += 2; k += 2;</div>
<div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;  }</div>
<div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;  <span class="keywordflow">if</span>(K - k &gt;= 1) {</div>
<div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160;    urolls::template transB_kernel&lt;1, toTemp, remM&gt;(B_arr + k*LDB, LDB, B_temp, LDB_, ymm, remM_);</div>
<div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;    B_temp += 1; k += 1;</div>
<div class="line"><a name="l00828"></a><span class="lineno">  828</span>&#160;  }</div>
<div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;}</div>
<div class="line"><a name="l00830"></a><span class="lineno">  830</span>&#160; </div>
<div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keywordtype">bool</span> isARowMajor = true, <span class="keywordtype">bool</span> isBRowMajor = true, <span class="keywordtype">bool</span> isFWDSolve = true, <span class="keywordtype">bool</span> isUnitDiag = false&gt;</div>
<div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;<span class="keywordtype">void</span> triSolve(Scalar *A_arr, Scalar *B_arr, int64_t M, int64_t numRHS, int64_t LDA, int64_t LDB) {</div>
<div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;  <span class="keyword">const</span> int64_t kB = (3*packet_traits&lt;Scalar&gt;::size)*5; <span class="comment">// 5*U3</span></div>
<div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;  <span class="keyword">const</span> int64_t numM = 64;</div>
<div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160; </div>
<div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;  int64_t sizeBTemp = 0;</div>
<div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160;  Scalar *B_temp = NULL;</div>
<div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;  EIGEN_IF_CONSTEXPR(!isBRowMajor) {</div>
<div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;    sizeBTemp = (((std::min(kB, numRHS) + 15)/16+ 4)*16)*numM;</div>
<div class="line"><a name="l00885"></a><span class="lineno">  885</span>&#160;    B_temp = (Scalar*) aligned_alloc(4096,<span class="keyword">sizeof</span>(Scalar)*sizeBTemp);</div>
<div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;  }</div>
<div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;  <span class="keywordflow">for</span>(int64_t k = 0; k &lt; numRHS; k += kB) {</div>
<div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;    int64_t bK = numRHS - k &gt; kB ? kB : numRHS - k;</div>
<div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;    int64_t M_ = (M/EIGEN_AVX_MAX_NUM_ROW)*EIGEN_AVX_MAX_NUM_ROW, gemmOff = 0;</div>
<div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160; </div>
<div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;    <span class="comment">// bK rounded up to next multiple of L=EIGEN_AVX_MAX_NUM_ROW. When B_temp is used, we solve for bkL RHS</span></div>
<div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;    <span class="comment">// instead of bK RHS in triSolveKernelLxK.</span></div>
<div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;    int64_t bkL = ((bK + (EIGEN_AVX_MAX_NUM_ROW-1))/EIGEN_AVX_MAX_NUM_ROW)*EIGEN_AVX_MAX_NUM_ROW;</div>
<div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;    <span class="keyword">const</span> int64_t numScalarPerCache = 64/<span class="keyword">sizeof</span>(Scalar);</div>
<div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;    <span class="comment">// Leading dimension of B_temp, will be a multiple of the cache line size.</span></div>
<div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;    int64_t LDT = ((bkL+(numScalarPerCache-1))/numScalarPerCache)*numScalarPerCache;</div>
<div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;    int64_t offsetBTemp = 0;</div>
<div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;    <span class="keywordflow">for</span>(int64_t i = 0; i &lt; M_; i += EIGEN_AVX_MAX_NUM_ROW) {</div>
<div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;      EIGEN_IF_CONSTEXPR(!isBRowMajor) {</div>
<div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160;        int64_t indA_i  = isFWDSolve ? i           : M - 1 - i;</div>
<div class="line"><a name="l00901"></a><span class="lineno">  901</span>&#160;        int64_t indB_i  = isFWDSolve ? i           : M - (i + EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;        int64_t offB_1  = isFWDSolve ? offsetBTemp : sizeBTemp - EIGEN_AVX_MAX_NUM_ROW*LDT - offsetBTemp;</div>
<div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160;        int64_t offB_2  = isFWDSolve ? offsetBTemp : sizeBTemp - LDT - offsetBTemp;</div>
<div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;        <span class="comment">// Copy values from B to B_temp.</span></div>
<div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;        copyBToRowMajor&lt;Scalar, true, false&gt;(B_arr + indB_i + k*LDB, LDB, bK, B_temp + offB_1, LDT);</div>
<div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;        <span class="comment">// Triangular solve with a small block of A and long horizontal blocks of B (or B_temp if B col-major)</span></div>
<div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;        triSolveKernelLxK&lt;Scalar, isARowMajor, isFWDSolve, isUnitDiag&gt;(</div>
<div class="line"><a name="l00908"></a><span class="lineno">  908</span>&#160;          &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i, indA_i, LDA)], B_temp + offB_2, EIGEN_AVX_MAX_NUM_ROW, bkL, LDA, LDT);</div>
<div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160;        <span class="comment">// Copy values from B_temp back to B. B_temp will be reused in gemm call below.</span></div>
<div class="line"><a name="l00910"></a><span class="lineno">  910</span>&#160;        copyBToRowMajor&lt;Scalar, false, false&gt;(B_arr + indB_i + k*LDB, LDB, bK, B_temp + offB_1, LDT);</div>
<div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160; </div>
<div class="line"><a name="l00912"></a><span class="lineno">  912</span>&#160;        offsetBTemp += EIGEN_AVX_MAX_NUM_ROW*LDT;</div>
<div class="line"><a name="l00913"></a><span class="lineno">  913</span>&#160;      }</div>
<div class="line"><a name="l00914"></a><span class="lineno">  914</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00915"></a><span class="lineno">  915</span>&#160;        int64_t ind = isFWDSolve ? i : M - 1 - i;</div>
<div class="line"><a name="l00916"></a><span class="lineno">  916</span>&#160;        triSolveKernelLxK&lt;Scalar, isARowMajor, isFWDSolve, isUnitDiag&gt;(</div>
<div class="line"><a name="l00917"></a><span class="lineno">  917</span>&#160;          &amp;A_arr[idA&lt;isARowMajor&gt;(ind, ind, LDA)], B_arr + k + ind*LDB, EIGEN_AVX_MAX_NUM_ROW, bK, LDA, LDB);</div>
<div class="line"><a name="l00918"></a><span class="lineno">  918</span>&#160;      }</div>
<div class="line"><a name="l00919"></a><span class="lineno">  919</span>&#160;      <span class="keywordflow">if</span>(i+EIGEN_AVX_MAX_NUM_ROW &lt; M_) {</div>
<div class="line"><a name="l00932"></a><span class="lineno">  932</span>&#160;        EIGEN_IF_CONSTEXPR(isBRowMajor) {</div>
<div class="line"><a name="l00933"></a><span class="lineno">  933</span>&#160;          int64_t indA_i  = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW : M - (i + 2*EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;          int64_t indA_j  = isFWDSolve ? 0                         : M - (i + EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160;          int64_t indB_i  = isFWDSolve ? 0                         : M - (i + EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;          int64_t indB_i2 = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW : M - (i + 2*EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;          gemmKernel&lt;Scalar,isARowMajor, isBRowMajor,false,false&gt;(</div>
<div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160;            &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i,indA_j,LDA)],</div>
<div class="line"><a name="l00939"></a><span class="lineno">  939</span>&#160;            B_arr + k + indB_i*LDB,</div>
<div class="line"><a name="l00940"></a><span class="lineno">  940</span>&#160;            B_arr + k + indB_i2*LDB,</div>
<div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;            EIGEN_AVX_MAX_NUM_ROW, bK, i + EIGEN_AVX_MAX_NUM_ROW,</div>
<div class="line"><a name="l00942"></a><span class="lineno">  942</span>&#160;            LDA, LDB, LDB);</div>
<div class="line"><a name="l00943"></a><span class="lineno">  943</span>&#160;        }</div>
<div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;        <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00945"></a><span class="lineno">  945</span>&#160;          <span class="keywordflow">if</span>(offsetBTemp + EIGEN_AVX_MAX_NUM_ROW*LDT &gt; sizeBTemp) {</div>
<div class="line"><a name="l00954"></a><span class="lineno">  954</span>&#160;            int64_t indA_i = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW   : 0;</div>
<div class="line"><a name="l00955"></a><span class="lineno">  955</span>&#160;            int64_t indA_j = isFWDSolve ? gemmOff                     : M - (i + EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00956"></a><span class="lineno">  956</span>&#160;            int64_t indB_i = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW   : 0;</div>
<div class="line"><a name="l00957"></a><span class="lineno">  957</span>&#160;            int64_t offB_1 = isFWDSolve ? 0                           : sizeBTemp - offsetBTemp;</div>
<div class="line"><a name="l00958"></a><span class="lineno">  958</span>&#160;            gemmKernel&lt;Scalar,isARowMajor, isBRowMajor,false,false&gt;(</div>
<div class="line"><a name="l00959"></a><span class="lineno">  959</span>&#160;              &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i, indA_j,LDA)],</div>
<div class="line"><a name="l00960"></a><span class="lineno">  960</span>&#160;              B_temp + offB_1,</div>
<div class="line"><a name="l00961"></a><span class="lineno">  961</span>&#160;              B_arr + indB_i + (k)*LDB,</div>
<div class="line"><a name="l00962"></a><span class="lineno">  962</span>&#160;              M - (i + EIGEN_AVX_MAX_NUM_ROW), bK, i + EIGEN_AVX_MAX_NUM_ROW - gemmOff,</div>
<div class="line"><a name="l00963"></a><span class="lineno">  963</span>&#160;              LDA, LDT, LDB);</div>
<div class="line"><a name="l00964"></a><span class="lineno">  964</span>&#160;            offsetBTemp = 0; gemmOff = i + EIGEN_AVX_MAX_NUM_ROW;</div>
<div class="line"><a name="l00965"></a><span class="lineno">  965</span>&#160;          }</div>
<div class="line"><a name="l00966"></a><span class="lineno">  966</span>&#160;          <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00970"></a><span class="lineno">  970</span>&#160;            int64_t indA_i = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW   : M - (i + 2*EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00971"></a><span class="lineno">  971</span>&#160;            int64_t indA_j = isFWDSolve ? gemmOff                     : M - (i + EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00972"></a><span class="lineno">  972</span>&#160;            int64_t indB_i = isFWDSolve ? i + EIGEN_AVX_MAX_NUM_ROW   : M - (i + 2*EIGEN_AVX_MAX_NUM_ROW);</div>
<div class="line"><a name="l00973"></a><span class="lineno">  973</span>&#160;            int64_t offB_1 = isFWDSolve ? 0                           : sizeBTemp - offsetBTemp;</div>
<div class="line"><a name="l00974"></a><span class="lineno">  974</span>&#160;            gemmKernel&lt;Scalar,isARowMajor, isBRowMajor,false,false&gt;(</div>
<div class="line"><a name="l00975"></a><span class="lineno">  975</span>&#160;              &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i,indA_j,LDA)],</div>
<div class="line"><a name="l00976"></a><span class="lineno">  976</span>&#160;              B_temp + offB_1,</div>
<div class="line"><a name="l00977"></a><span class="lineno">  977</span>&#160;              B_arr + indB_i + (k)*LDB,</div>
<div class="line"><a name="l00978"></a><span class="lineno">  978</span>&#160;              EIGEN_AVX_MAX_NUM_ROW, bK, i + EIGEN_AVX_MAX_NUM_ROW - gemmOff,</div>
<div class="line"><a name="l00979"></a><span class="lineno">  979</span>&#160;              LDA, LDT, LDB);</div>
<div class="line"><a name="l00980"></a><span class="lineno">  980</span>&#160;          }</div>
<div class="line"><a name="l00981"></a><span class="lineno">  981</span>&#160;        }</div>
<div class="line"><a name="l00982"></a><span class="lineno">  982</span>&#160;      }</div>
<div class="line"><a name="l00983"></a><span class="lineno">  983</span>&#160;    }</div>
<div class="line"><a name="l00984"></a><span class="lineno">  984</span>&#160;    <span class="comment">// Handle M remainder..</span></div>
<div class="line"><a name="l00985"></a><span class="lineno">  985</span>&#160;    int64_t bM = M-M_;</div>
<div class="line"><a name="l00986"></a><span class="lineno">  986</span>&#160;    <span class="keywordflow">if</span> (bM &gt; 0){</div>
<div class="line"><a name="l00987"></a><span class="lineno">  987</span>&#160;      <span class="keywordflow">if</span>( M_ &gt; 0) {</div>
<div class="line"><a name="l00988"></a><span class="lineno">  988</span>&#160;        EIGEN_IF_CONSTEXPR(isBRowMajor) {</div>
<div class="line"><a name="l00989"></a><span class="lineno">  989</span>&#160;          int64_t indA_i  = isFWDSolve ? M_ : 0;</div>
<div class="line"><a name="l00990"></a><span class="lineno">  990</span>&#160;          int64_t indA_j  = isFWDSolve ? 0  : bM;</div>
<div class="line"><a name="l00991"></a><span class="lineno">  991</span>&#160;          int64_t indB_i  = isFWDSolve ? 0  : bM;</div>
<div class="line"><a name="l00992"></a><span class="lineno">  992</span>&#160;          int64_t indB_i2 = isFWDSolve ? M_ : 0;</div>
<div class="line"><a name="l00993"></a><span class="lineno">  993</span>&#160;          gemmKernel&lt;Scalar,isARowMajor, isBRowMajor,false,false&gt;(</div>
<div class="line"><a name="l00994"></a><span class="lineno">  994</span>&#160;            &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i,indA_j,LDA)],</div>
<div class="line"><a name="l00995"></a><span class="lineno">  995</span>&#160;            B_arr + k +indB_i*LDB,</div>
<div class="line"><a name="l00996"></a><span class="lineno">  996</span>&#160;            B_arr + k + indB_i2*LDB,</div>
<div class="line"><a name="l00997"></a><span class="lineno">  997</span>&#160;            bM , bK, M_,</div>
<div class="line"><a name="l00998"></a><span class="lineno">  998</span>&#160;            LDA, LDB, LDB);</div>
<div class="line"><a name="l00999"></a><span class="lineno">  999</span>&#160;        }</div>
<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160;        <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160;          int64_t indA_i = isFWDSolve ? M_      : 0;</div>
<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160;          int64_t indA_j = isFWDSolve ? gemmOff : bM;</div>
<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;          int64_t indB_i = isFWDSolve ? M_      : 0;</div>
<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160;          int64_t offB_1 = isFWDSolve ? 0       : sizeBTemp - offsetBTemp;</div>
<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160;          gemmKernel&lt;Scalar,isARowMajor, isBRowMajor,false,false&gt;(</div>
<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160;            &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i,indA_j,LDA)],</div>
<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>&#160;            B_temp + offB_1,</div>
<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>&#160;            B_arr + indB_i + (k)*LDB,</div>
<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>&#160;            bM , bK, M_ - gemmOff,</div>
<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160;            LDA, LDT, LDB);</div>
<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160;        }</div>
<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160;      }</div>
<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>&#160;      EIGEN_IF_CONSTEXPR(!isBRowMajor) {</div>
<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160;        int64_t indA_i  = isFWDSolve ? M_ : M - 1 - M_;</div>
<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>&#160;        int64_t indB_i  = isFWDSolve ? M_ : 0;</div>
<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>&#160;        int64_t offB_1  = isFWDSolve ? 0  : (bM-1)*bkL;</div>
<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>&#160;        copyBToRowMajor&lt;Scalar, true,  true&gt;(B_arr + indB_i + k*LDB, LDB, bK, B_temp, bkL, bM);</div>
<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>&#160;        triSolveKernelLxK&lt;Scalar, isARowMajor, isFWDSolve, isUnitDiag&gt;(</div>
<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160;          &amp;A_arr[idA&lt;isARowMajor&gt;(indA_i, indA_i, LDA)], B_temp + offB_1, bM, bkL, LDA, bkL);</div>
<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160;        copyBToRowMajor&lt;Scalar, false, true&gt;(B_arr + indB_i + k*LDB, LDB, bK, B_temp, bkL, bM);</div>
<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160;      }</div>
<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160;      <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>&#160;        int64_t ind = isFWDSolve ? M_ : M - 1 - M_;</div>
<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160;        triSolveKernelLxK&lt;Scalar, isARowMajor, isFWDSolve, isUnitDiag&gt;(</div>
<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160;          &amp;A_arr[idA&lt;isARowMajor&gt;(ind, ind, LDA)], B_arr + k + ind*LDB, bM, bK, LDA, LDB);</div>
<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160;      }</div>
<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160;    }</div>
<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160;  }</div>
<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160;  EIGEN_IF_CONSTEXPR(!isBRowMajor) free(B_temp);</div>
<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160;}</div>
<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160; </div>
<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keywordtype">bool</span> isARowMajor = true, <span class="keywordtype">bool</span> isCRowMajor = true&gt;</div>
<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>&#160;<span class="keywordtype">void</span> gemmKer(Scalar *A_arr, Scalar *B_arr, Scalar *C_arr,</div>
<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;                int64_t M, int64_t N, int64_t K,</div>
<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160;                int64_t LDA, int64_t LDB, int64_t LDC) {</div>
<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160;  gemmKernel&lt;Scalar, isARowMajor, isCRowMajor, true, true&gt;(B_arr, A_arr, C_arr, N, M, K, LDB, LDA, LDC);</div>
<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160;}</div>
<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160; </div>
<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160; </div>
<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160;<span class="comment">// Template specializations of trsmKernelL/R for float/double and inner strides of 1.</span></div>
<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160;<span class="preprocessor">#if defined(EIGEN_USE_AVX512_TRSM_KERNELS)</span></div>
<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">bool</span> Conjugate, <span class="keywordtype">int</span> TriStorageOrder,<span class="keywordtype">int</span> OtherInnerStr<span class="keywordtype">id</span>e&gt;</div>
<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;<span class="keyword">struct </span>trsm_kernels;</div>
<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160; </div>
<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160;<span class="keyword">struct </span>trsm_kernels&lt;float, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>, Mode, false, TriStorageOrder, 1&gt;{</div>
<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> trsmKernelL(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize, <span class="keyword">const</span> <span class="keywordtype">float</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160;    <span class="keywordtype">float</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride);</div>
<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> trsmKernelR(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize, <span class="keyword">const</span> <span class="keywordtype">float</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160;    <span class="keywordtype">float</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride);</div>
<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160;};</div>
<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160; </div>
<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160;<span class="keyword">struct </span>trsm_kernels&lt;double, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>, Mode, false, TriStorageOrder, 1&gt;{</div>
<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> trsmKernelL(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize, <span class="keyword">const</span> <span class="keywordtype">double</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160;    <span class="keywordtype">double</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride);</div>
<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> trsmKernelR(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize, <span class="keyword">const</span> <span class="keywordtype">double</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160;    <span class="keywordtype">double</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride);</div>
<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>&#160;};</div>
<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160; </div>
<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>&#160;EIGEN_DONT_INLINE <span class="keywordtype">void</span> trsm_kernels&lt;float, Index, Mode, false, TriStorageOrder, 1&gt;::trsmKernelL(</div>
<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160;  <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize,</div>
<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160;  <span class="keywordtype">float</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride)</div>
<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160;{</div>
<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160;  EIGEN_UNUSED_VARIABLE(otherIncr);</div>
<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;  triSolve&lt;float, TriStorageOrder==RowMajor, false, (Mode&amp;Lower)==Lower, (Mode &amp; UnitDiag)!=0&gt;(</div>
<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160;    <span class="keyword">const_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(_tri), _other, size, otherSize, triStride, otherStride);</div>
<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;}</div>
<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160; </div>
<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;EIGEN_DONT_INLINE <span class="keywordtype">void</span> trsm_kernels&lt;float, Index, Mode, false, TriStorageOrder, 1&gt;::trsmKernelR(</div>
<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160;    <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize,</div>
<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">float</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160;    <span class="keywordtype">float</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride)</div>
<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;{</div>
<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;  EIGEN_UNUSED_VARIABLE(otherIncr);</div>
<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;  triSolve&lt;float, TriStorageOrder!=RowMajor, true, (Mode&amp;Lower)!=Lower, (Mode &amp; UnitDiag)!=0&gt;(</div>
<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160;    <span class="keyword">const_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(_tri), _other, size, otherSize, triStride, otherStride);</div>
<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160;}</div>
<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160; </div>
<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160;EIGEN_DONT_INLINE <span class="keywordtype">void</span> trsm_kernels&lt;double, Index, Mode, false, TriStorageOrder, 1&gt;::trsmKernelL(</div>
<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160;  <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize,</div>
<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">double</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160;  <span class="keywordtype">double</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride)</div>
<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>&#160;{</div>
<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>&#160;  EIGEN_UNUSED_VARIABLE(otherIncr);</div>
<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>&#160;  triSolve&lt;double, TriStorageOrder==RowMajor, false, (Mode&amp;Lower)==Lower, (Mode &amp; UnitDiag)!=0&gt;(</div>
<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160;    <span class="keyword">const_cast&lt;</span><span class="keywordtype">double</span>*<span class="keyword">&gt;</span>(_tri), _other, size, otherSize, triStride, otherStride);</div>
<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>&#160;}</div>
<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160; </div>
<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Index, <span class="keywordtype">int</span> Mode, <span class="keywordtype">int</span> TriStorageOrder&gt;</div>
<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160;EIGEN_DONT_INLINE <span class="keywordtype">void</span> trsm_kernels&lt;double, Index, Mode, false, TriStorageOrder, 1&gt;::trsmKernelR(</div>
<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160;    <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherSize,</div>
<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">double</span>* _tri, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> triStride,</div>
<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160;    <span class="keywordtype">double</span>* _other, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherIncr, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> otherStride)</div>
<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160;{</div>
<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160;  EIGEN_UNUSED_VARIABLE(otherIncr);</div>
<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160;  triSolve&lt;double, TriStorageOrder!=RowMajor, true, (Mode&amp;Lower)!=Lower, (Mode &amp; UnitDiag)!=0&gt;(</div>
<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160;    <span class="keyword">const_cast&lt;</span><span class="keywordtype">double</span>*<span class="keyword">&gt;</span>(_tri), _other, size, otherSize, triStride, otherStride);</div>
<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160;}</div>
<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>&#160;<span class="preprocessor">#endif </span><span class="comment">//EIGEN_USE_AVX512_TRSM_KERNELS</span></div>
<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>&#160;}</div>
<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>&#160;}</div>
<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>&#160;<span class="preprocessor">#endif </span><span class="comment">//EIGEN_TRSM_KERNEL_IMPL_H</span></div>
<div class="ttc" id="anamespaceEigen_html"><div class="ttname"><a href="namespaceEigen.html">Eigen</a></div><div class="ttdoc">Namespace containing all symbols from the Eigen library.</div><div class="ttdef"><b>Definition:</b> Core:139</div></div>
<div class="ttc" id="anamespaceEigen_html_a62e77e0933482dafde8fe197d9a2cfde"><div class="ttname"><a href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Eigen::Index</a></div><div class="ttdeci">EIGEN_DEFAULT_DENSE_INDEX_TYPE Index</div><div class="ttdoc">The Index type as used for the API.</div><div class="ttdef"><b>Definition:</b> Meta.h:59</div></div>
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